|Title||CISC849 Autonomous Robot Vision|
|Description||Survey of color camera, depth camera (e.g., Kinect), and laser range-finder-based 2-D and 3-D sensing algorithms for mobile robot navigation and interaction. Focus applications will be humanoid robot perception for disaster response, driverless cars, and trail following|
|When||Mondays and Wednesdays, 11 am-12 pm|
|Instructor||Christopher Rasmussen, 446 Smith Hall, firstname.lastname@example.org|
|Office hours||Tuesdays and Thursdays, 3:30-4:15 pm|
|Academic policies||Programming projects are due by midnight of the deadline day (with a grace period of a few hours afterward...after sunrise is definitely late). A late homework is a 0 without a valid prior excuse. To give you a little flexibility, you have 6 "late days" to use on homeworks to extend the deadline by one day each without penalty. No more than three late days may be used per assignment. Late days will automatically be subtracted, but as a courtesy please notify the instructor in an e-mail of your intention to use late days before the deadline. See submission instructions below.
Students can discuss problems with one another in general terms, but must work independently on programming assignments. This also applies to online and printed resources: you may consult them as references (as long as you cite them), but the words and source code you turn in must be yours alone. The University's policies on academic dishonesty are set forth in the student code of conduct here.
|Homeworks||Assignment submissions should consist of a directory containing all code (your .cpp files, makefile, etc.), any output data generated (e.g., images, movies, etc.), and an explanation of your approach, what worked and didn't work, etc. contained in a separate text or HTML file. Do not submit executables or .o files, please! The directory you submit for each assignment should be packaged by tar'ing and gzip'ing it or just zip'ing it. The resulting file should be submitted through Sakai.
You may develop your C/C++ code in any fashion that is convenient--that is, with any compiler and operating system that you want. However, we will be grading your homework on a Linux system with a makefile, and so you must avoid OS- and hardware-specific functions and provide a makefile for us that will work (like one of the templates above).
Possible Papers to Present (not a complete list)
- "Vision and Learning for Deliberative Monocular Cluttered Flight", D. Dey, K. Shankar, et al., FSR 2015. UAV, obstacle avoidance
- "Pushbroom Stereo for High-Speed Navigation in Cluttered Environments", A. Barry and R. Tedrake, ICRA 2015. UAV, obstacle avoidance
- "Collaborative mapping of an earthquake-damaged building via ground and aerial robots", N. Michael et al., JFR 2012. UAV, UGV, disaster, mapping
- "Vision Based Victim Detection from Unmanned Aerial Vehicles", M. Andriluka et al., IROS 2010. UAV, person detection
- "Biped Navigation in Rough Environments using On-board Sensing", J. Chestnutt, Y. Takaoka, K. Suga, K. Nishiwaki, J. Kuffner, and S. Kagami, IROS 2009. Footstep planning, ladar, plane fitting
- "Real-Time Navigation in 3D Environments Based on Depth Camera Data", D. Maier, A. Hornung, and M. Bennewitz, Humanoids 2012. RGB-D, localization, mapping, planning
- "Robotic Grasping of Novel Objects using Vision", A. Saxena, J. Driemeyer, A. Ng, IJRR 2008. Grasping, learning
- "Self-supervised Monocular Road Detection in Desert Terrain", H. Dahlkamp, A. Kaehler, D. Stavens, S. Thrun, and G. Bradski, 2006. DARPA GC, color similarity, segmentation
- "Multi-Sensor Lane Finding in Urban Road Networks", A. Huang, D. Moore, M. Antone, E. Olson, S. Teller, RSS 2008. DARPA UC, edge detection, robust curve fitting, tracking
- "High fidelity day/night stereo mapping with vegetation and negative obstacle detection for vision-in-the-loop walking", M. Bajracharya et al., IROS 2013. LS3, dense stereo depth, visual odometry
- "Autonomous Door Opening and Plugging In with a Personal Robot", W. Meeussen et al., IROS 2010. PR2, grasping
|Both of the following libraries are available for Linux, Windows, and Mac OS. For (relative) simplicity, we will not be installing ROS (which includes both)|
Note: The blue squares in the "#" column below indicate Tuesdays.
|2||Feb. 11||Finish background; introduction to the DARPA Robotics Challenge||"How South Korea's DRC-HUBO Robot Won the DARPA Robotics Challenge", IEEE Spectrum, June 9, 2015||slides|
|3||Feb. 16||DRC algorithm components||slides|
Register/add deadline Feb. 24
|PCL tutorial||RANSAC background||slides|
|5||Feb. 23||Plane/obstacle/object segmentation (3-D), clustering, ICP||slides|
|6||Feb. 25||NOVA "Rise of the Robots"||Next generation Atlas|
|7||Mar. 1||Finish ICP/registration; trail-following overview||slides|
|8||Mar. 3||Trail-following algorithmic components||slides|
HW #1 due
|9||Mar. 8||Tracking, localization||Thrun particle filtering slides||slides|
|10||Mar. 10||Particle filtering||OpenCV installation||slides|
|11||Mar. 15||Intro to OpenCV||Mats, drawing, background subtraction, thresholding and erosion/dilation||slides|
|12||Mar. 17||More on OpenCV; object recognition (sample paper)||Connected components, bounding rect, tracker API; "Real-Time Human Pose Recognition in Parts from Single Depth Images", J. Shotton et al., CVPR 2011. Recognition, classification, RGB-D||slides|
|13||Mar. 22||Finish Kinect body part recognition paper|
|14||Mar. 24||Survey paper choices||slides|
Paper presentation choice due Friday, March 25
HW #2 due
|Mar. 29||NO CLASS
|Mar. 31||NO CLASS
|15||Apr. 5||Intro. to motion planning||slides|
|16||Apr. 7||NO CLASS
|Apr. 12||Student paper presentations||C. Rasmussen, "Learning Locomotion over Rough Terrain using Terrain Templates", M. Kalakrishnan, J. Buchli, P. Pastor, and S. Schaal, IROS 2009
K. Eckenhoff, "Collaborative mapping of an earthquake-damaged building via ground and aerial robots"
|Project proposal due|
|17||Apr. 14||Student paper presentations||P. Cao, "Vision and learning for Deliberative Monocular Cluttered Flight"
S. Veer, "Biped Navigation in Rough Environments using On-board Sensing"
|Student paper presentations||S. Khan, "Self-supervised monocular Road Detection in Desert Terrain"
M. Kaplan, "Linear Auto-Calibration..."
|19||Apr. 21||Student paper presentations||M. Zhou, "Pushbroom Stereo for High-Speed Navigation..."
W. Treible and K. Corder, "Real-Time Navigation in 3D Environments Based on Depth Camera Data"
|20||Apr. 26||Mid-project review|
|21||Apr. 28||Mapping||SLAM demos: Pirobot, MIT, Darmstadt "Hector" mapping
"Real-Time SLAM with Octree Evidence Grids for Exploration in Underwater Tunnels", N. Fairfield, G. Kantor, and D. Wettergreen, JFR 2007
|22||May 3||DARPA Urban Challenge||Long video, highlights only, Stanford clips||Team presentations from ICRA 2008 workshop|
|23||May 5||Final project review|
|24||May 10||"Bonus" material|
|25||May 12||NO CLASS
Finish your project!
|26||May 17||Final project presentations -- class starts at 10 am||Final project due|